Category Archives: Marketing / Tech Interface

Lab Store: Panic Pack!

Lab Store, Marketing / Tech Interface

The average ecommerce / catalog packer can pack about 22 – 25 boxes an hour, depending on the level of automation.  Of course, we don’t have anything like traditional mail order automation in the Lab Store; just a computer, a printer and my wife Barb as Chief Packer & Chief Customer Officer.  I pitch in by assembling products and generally keeping the “warehouse” shelves stocked so the Chief can do her thing with the packages and customers.

For a variety of reasons we got a late start today packing the orders from over the weekend and New Year’s Eve / Day, and had to invoke a “Panic Pack” on these 131 orders.  A Panic Pack is a high speed affair where Barb picks all the orders but leaves some for me to pack (I suck at packing compared with her) while she packs the others.  We packed all 131 orders in 4 hours, just barely in time for UPS pickup.

UPS Receipt

That might not sound like a big deal versus the 25 boxes an hour, but remember we are also picking the orders and dealing with all the customer service – can you add this to my order, can you change my shipping method, etc.  Most packers simply pack an order that has already been picked for them, and don’t do any customer service.

131 packages

My point with this post is not that we know how to pack like banshees, but the enabling technology behind this capability.

It would have been impossible to pack and manage the service with this many orders in such a short time without a proper backend order management system – something I see many ecommerce folks go without.  Most web-based cart back-ends are incredibly difficult to deal with, especially on order changes.

In many web-based order processing systems, it can take multiple steps to make simple changes rather than just a few clicks – add another product to an order, run another credit card charge, reprint the packing slips, etc.  This is because once an order is processed, it’s not meant to be changed; order changes were not taken into account when these systems were designed.  Nobody talked to customer service to get specs, I guess…

“You mean customers might want to change an order they already placed?  Why?”  ‘Cause most of them are not geeks.  They make mistakes.  They forget stuff.

Often, when you call companies using these systems to add products to your order, they tell you “we can’t” and to go online and place another order.  Nice.  Great service.

We actually don’t mind if customers want to add to orders they have already placed with us – silly, huh?  Gee, you want to spend more money with us?  Sure, bring it on!  By the way, Flat Rate shipping encourages this behavior.

If you have a good backend system, you can just add the product and the software does the rest, because the order has not been “processed” yet as it has with web-based systems – you process the order right before you print the packing slips, including the credit card capture.  And, you can do all kinds of customization on the packing slip, like messaging for new customers, repeat customers, and so forth, and automatically interface with the shipping manifest system.

The labor cost savings alone when using these order management systems is huge.  When we moved from web-based “copy & paste” order management to local software, our time spent per order on customer service dropped by 50%.  This kind of gain in productivity is common, as you can see here.

And when you have more time to service each customer, you  can provide better, more customized service.  Simple as that.

Plus, our backend system creates one heck of a customer database, automatically consolidating orders at the customer level and providing one-click access to customer service history, cumulative sales, and so forth.  Whenever we are faced with a complex service issue, the first thing we do is look at the cumulative sales of the customer, and then we act accordingly.  In other words, for proven good customers, we bend the rules.  That’s how you build loyalty.

So you need a customer database to provide great service.  As far as Marketing goes, you need a customer database to measure the success of customer-centric programs like this one and this one.

If you don’t have a flexible and marketing friendly order management system, you really should consider getting one.  We use Stone Edge.

Messaging for Engagement

DataBase Marketing, Marketing / Tech Interface, Web Analytics

Or Behavioral Messaging, as we used to call it. 

Much has been written about Measuring Engagement, but once you measure it, then what do you do with this information?  Most folks know the idea driving the Engagement Movement is to make your messaging more Relevant, but how do you implement?  Perhaps you can find the triggers with a behavioral measurement, but then what do you say?

This is the part Marketing folks typically get wrong on the execution side.  They might have a nice behavioral segmentation, but then crush the value of that hard analytical work by sending a demographically-oriented message, often because that is really all they know how to do.  So as an analyst, how to you raise this issue or effect change?

Marketing messaging can be a complex topic, but there are some baseline ideas you can use.  Start here, then do what you do best – analyze the results, test, repeat.

You want to think of customers as being in different “states” or “stages” along an engagement continuum.  For example:

  • Engaged – highly positive on company, very willing to interact – Highest Potential Value
  • Apathetic – don’t really care one way or the other, will interact when prompted – Medium Potential Value
  • Detached – not really interested, don’t think they need product or service anymore – Lowest Potential Value

Please note that none of these states have anything to do with demographics – they are about emotions.  The messaging should relate to visitor / customer experience as expressed through behavior, not age and income.

These states are in flux and you can affect state by using the appropriate message based on the behavioral analysis.  Customers generally all start out being Engaged (which is why a New Customer Kit works so well), then drop down through the stages.  The rate of this drop generally depends on the product / service experience – the Customer LifeCycle.

Generically, this approach sets up what is known as “right message, to the right person, at the right time” or trigger-based messaging.  Just think about your own experience interacting with different companies; for each company, you could probably select the state you are in right now!

OK, so for each state there is an appropriate message approach:

Engaged – Kiss Messaging: We think you are the best.  Really.  We’d like to do something special for you – give you higher levels of service, create a special club for you, thank you profusely with free gifts.  Marketing Note: be creative, and avoid discounting to this group.  Save the discounts for the next two stages.

Apathetic – Date Messaging: We’re not real clear where we stand with you, so we’re going to be exploratory, test different ideas and see where the relationship stands.  Perhaps we can get you to be Engaged again?  In terms of ROI, this group has the highest incremental potential.  Example: this is where loyalty programs derive the most payback.

Detached – Bribe Messaging: You’re not really into this relationship, and we know that.  So we are simply going to make very strong offers to you and try to get you to respond.  A few of you might even become Engaged again.

Can you see how sending a generic message to all of these groups is sub-optimal?  Can you see how sending an Engaged message to the Detached group would probably generate a belly laugh as opposed to a response?  You’ve received this mis-messaged before stuff, right?  You basically hate the company for screwing you and then they send you a lovey-dovey Kiss message.  Makes you want to scream, you think, “Man, they are clueless!” and now you dislike the company even more.

Combine this messaging approach with a classic behavioral analysis, and you now have a strategy and tactic map.  For example, you know the longer it has been since someone purchased, clicked, opened, visited etc, the less likely they are to engage in that activity again.  Here’s the behavioral analysis with the messaging overlay:

Click image to enlarge…

Kiss Date Bribe

Please note “Months Since Last Contact” means the customer taking action and contacting you in some way (purchase, click) not the fact that you have tried to contact them! 

So does this make sense?  Those most likely to respond are messaged as Engaged – as is proper in terms of the relationship (left side of chart).  As they become less likely to respond, you should change the tone of your communication to fit the relationship up to a point, where quite frankly you should take a clue from the eMetrics Summit and not message them any more at all (right side of chart).

Example Campaign for the Engaged: At HSN, I came up with the idea of creating some kind of “Holiday Ornament” we could send to Engaged customers.  If the idea worked (meaning it generated incremental profit), we could do it as an annual thing; we could put the year on the ornament and create a “collectible” feel, which is the right idea for this audience.  No discount – just a “Thank You” message “for one of our best customers” and “Here’s a gift for you”.

These snowflake ornaments were about $1.20 in the mail (laser cut card stock) and generated about $5 in 90-day incremental profit per household with the Engaged, test versus control.  Why?  Good ‘ol Surprise and Delight, I would bet.

We had some test cells running to see how far we could take this, and as expected, the profitability dropped off dramatically based on how Engaged the customer was.  If the customer was even minimally dis-engaged – no purchase for over 120 days – there was very little effect. 

Interactivity cuts both ways; it’s great when customers are Engaged, but once the relationship starts to degrade, folks can move on very quickly emotionally.  That’s why it is so important to track this stuff – so you can predict when your audience is dis-engaging and do something about it.

Your Ad Here (Everywhere)

Marketing / Tech Interface

Seems like every day I hear about a new way to stick ads in front of people online or through a mobile device.

Every new business model is advertising-based and is going to attract billions of dollars.  Companies are out there buying other companies that are basically worth nothing for billions of dollars based on the promise of ad revenue.  This despite the fact (for example) social media advertising has really sucked – and is getting worse.  Plus, there’s the fact nobody will pay for social media services.

Further, ask yourself this question: what if social media advertising does suck and will always suck because it is simply always out of context?  To be clear, by context I mean not the content surrounding the ad, but from the end user perspective.  If people hate seeing your ads while they are trying to do personal stuff, won’t the advertising always be ineffective?  That fundamentally, the advertising model for this kind of content is flawed and will not get better? 

Can you say GeoCities?

This situation reminds me of the dot-com “ads on your car” thing, which got so ridiculous that companies were actually giving away FREE CARS to people as long as they drove them around with ads on them.  How do you ever pay that back?  And how are those ads effective?  I guess there are a ton of marketing rubes out there who will buy any ad just to get the “exposure” – regardless of how out of context the exposure is.  Do they still sell ads on matchbooks?

But let’s not stop there.  For some reason I can’t get the economics of supply and demand out of my head.  If every single display surface online becomes a display ad, doesn’t that mean there will be an unlimited supply of online display advertising and so the value of online display ads will drop close to zero?  Perhaps a lot closer to the economic value most of these ads provide?

You tell me.

At least with eyeblack advertising, there is a limited supply – teams on televised sporting events (TV is actually the media, not the eyeblack).  That is, until somebody comes up with the idea of paying people to wear eyeblack ads – which can’t be too far away, can it?

Hey, I have an idea…want to make a billion dollars?  Know any marketing people just dying to buy this kind of “walking around” media?  Fortunately, I think the buy side has pushed back and is a lot smarter as a whole.

The above is not to say that specific exotic media will not work for certain very targeted applications.  The problem is in thinking any of this media is “mass” in nature, that it will be able to move the needle.  If the applications for this advertising are very narrow, then only certain narrow portions of the inventory have value, meaning the value of the companies is a lot lower than what is perceived.

Personally, I think the same thing will happen in mobile.  The killer advertising app for mobile is search, not display or audio, whether geo-intelligent or not.  Search fits the context of the user, just as search does online.  Free mobile services if you listen to an ad first?  C’mon folks, that model has been played and played online and it never works.  The combination of audience quality and the notion of being “forced” to pay attention do not equal great advertising results.

Your Ad Everywhere, as a whole, is an economically broken business model that delivers little value to either the advertiser or the audience.  Let’s just stop creating business models based solely on delivering display ads to people.

I suggest to you the test for the viability of an “network effect” display ad business model is very simple: ask the audience, would you pay for this service / application / access?  If the answer is no, the audience is not a viable advertising audience.  If the answer is yes, then you can look for ways to reduce billing by introducing the right kind of advertising.  This means, of course, that these networks will be much smaller, but have a high quality audience worth advertising to.

If you start with free, you have already poisoned the audience for any ad model relying on “impressions”.